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How Well Can We Estimate Pedersen Conductance 10.1029/2018JA026067 from the THEMIS White‐Light All‐Sky Cameras? Key Points: M

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How Well Can We Estimate Pedersen Conductance 10.1029/2018JA026067 from the THEMIS White‐Light All‐Sky Cameras? Key Points: M RESEARCH ARTICLE How Well Can We Estimate Pedersen Conductance 10.1029/2018JA026067 From the THEMIS White‐Light All‐Sky Cameras? Key Points: M. M. Lam1 , M. P. Freeman2 , C. M. Jackman1 , I. J. Rae3 , N. M. E. Kalmoni3 , • We use a white‐light all‐sky imager 3 3 to estimate Pedersen conductance to J. K. Sandhu , and C. Forsyth within an uncertainty of 3 mho or 1 2 40% Department of Physics and Astronomy, University of Southampton, Southampton, UK, British Antarctic Survey, • We relate Pedersen conductance to Cambridge, UK, 3Mullard Space Science Laboratory, University College London, London, UK the optical intensity with a single parabolic relationship across a wide range of geomagnetic activity Abstract We show that a white‐light all‐sky imager can estimate Pedersen conductance with an • Our results enable the exploitation of white‐light camera networks to uncertainty of 3 mho or 40%. Using a series of case studies over a wide range of geomagnetic activity, we study continental‐scale phenomena compare estimates of Pedersen conductance from the backscatter spectrum of the Poker Flat Incoherent such as substorms Scatter Radar with auroral intensities. We limit this comparison to an area bounding the radar measurements and within a limited area close to (but off) imager zenith. We confirm a linear relationship Supporting Information: • Supporting Information S1 between conductance and the square root of auroral intensity predicted from a simple theoretical approximation. Hence, we extend a previous empirical result found for green‐line emissions to the case of white‐light off‐zenith emissions. The difference between the radar conductance and the best‐fit relationship Correspondence to: has a mean of −0.76 ± 4.8 mho and a relative mean difference of 21% ± 78%. The uncertainties are M. M. Lam, reducedto−0.72±3.3mhoand0%±40% byaveragingconductanceover10min,whichweattributetothetime [email protected] that auroral features take to move across the imager field being greater than the 1‐min resolution of the radar data. Our results demonstrate and calibrate the use of Time History of Events and Macroscale Citation: InteractionsduringSubstormsall‐skyimagersforestimatingPedersenconductance.Thistechniqueallowsthe Lam, M. M., Freeman, M. P., Jackman, ‐ C. M., Rae, I. J., Kalmoni, N. M. E., extension of estimates of Pedersen conductance from Incoherent Scatter Radars to derive continental scale Sandhu, J. K., & Forsyth, C. (2019). estimates on scales of ~1–10 min and ~100 km2. It thus complements estimates from low‐altitude satellites, How well can we estimate Pedersen satellite auroral imagers, and ground‐based magnetometers. conductance from the THEMIS ‐ ‐ white light all sky cameras? Journal of Plain Language Summary The Sun is a rotating magnetic plasma ball that releases energetic Geophysical Research: Space Physics, “ ” “ ” 124. https://doi.org/10.1029/ charged particles and magnetism in a solar wind. Sometimes, this wind shakes hands with the Earth's 2018JA026067 magnetic field, allowing energy to be pumped into region near the Earth, stretching magnetic field lines like an elastic band. Much energy is released explosively in a “substorm” causing complex and brilliant Received 6 SEP 2018 auroral light displays about the size of a continent. This can be examined really well over several kilometers Accepted 6 MAR 2019 Accepted article online 12 MAR 2019 by radars on the ground. However, the radars cannot tell you what is happening for the whole substorm which is the size of a continent. It had been suggested that you can use a surface camera with a filter on it to estimate the part of the conductivity that tells us how much electric currents are heating the atmosphere. We asked whether the network of nonfiltered cameras stretching across North America could measure the conductivity as well as a radar can. We found they do half as well as the radar. This means we can use this camera network and its data archive to learn more about how much substorms heat up the atmosphere and how complicated and changeable this behavior is. 1. Introduction Ionospheric conductivity plays an important role in magnetosphere‐ionosphere coupling. For instance, the distributions of the ionospheric electric field and of the Pedersen conductance ΣP determine the Joule heat- ing of the ionosphere which has been estimated to dissipate over 50% of the total solar wind energy input to the Earth system (Østgaard et al., 2002). In addition, Joule heating is a key contributor to the power input into the thermosphere and thereby to the drag on satellites (e.g., Knipp et al., 2005). Solar irradiance and energetic particle precipitation (EPP) are both contributors to the ionospheric conductivity. The variation of the solar irradiance contribution is smooth and predictable and has a background Pedersen conductance of ~5 mho. In contrast, the EPP contribution is variable in time and space, especially during substorms (Clilverd et al., 2012). Some of the largest values of Pedersen conductance, of about 40–50 mho, have been associated with the intense auroral activity of the Westward Traveling Surge (e.g., Aikio & Kaila, 1996; ©2019. American Geophysical Union. All Rights Reserved. Kirkwood et al., 1988). Such surges can have a scale size of several hundreds of kilometers and move LAM ET AL. 1 Journal of Geophysical Research: Space Physics 10.1029/2018JA026067 across thousands of kilometers (Craven et al., 1989). In order to calculate Joule heating during intervals of EPP, knowledge of the conductance on as fine a spatial and temporal scale as possible over the region of interest is required. In the case of a substorm, the region of interest is of continental scale. The Pedersen conductance is difficult to routinely measure across a large area except by using global auroral satellite observations, which relies on there being an appropriate satellite in operation. Accurate specifica- tions of Pedersen conductance may be calculated from theory using observed values of electron density (e.g., Senior et al., 2007) and model‐derived values of ion‐neutral and electron‐neutral collision frequencies (Schunk & Nagy, 1978; Schunk & Walker, 1973). Observations of electron density from incoherent scatter radar (ISR) data sets such as those of the European Incoherent Scatter Scientific Association (EISCAT) and the Poker Flat ISR have been used to derive Pedersen conductivities in this way (e.g., Aikio & Kaila, 1996; Kaeppler et al., 2015; Kirkwood et al., 1988; Lester et al., 1996; Senior et al., 2008). The width of an ISR beam is typically ~1°, which corresponds to a horizontal distance of a few kilometers or less in the E region of the ionosphere. This should be contrasted to the spatial size associated with substorms. The size is variable (e.g., Murphy et al., 2011; Uritsky et al., 2002), but a mode analysis of 1 month of SuperMAG ground‐based magnetometer data indicates the extent of the DP1 system to be ~9 hr magnetic local time (MLT) and ~2.5° latitude (Figure 6 in Shore et al., 2017) which corresponds to ~6,000 km by ~300 km, at auroral latitudes. Clearly, an ISR's limited field of view cannot be used to estimate ΣP over such large spatial extents, leading to the compromise in the calculation of energy deposition rates (e.g., Rae et al., 2007) of using model conductances (e.g., Bilitza, 1990; Wallis & Budzinski, 1981). It is possible to extrapolate to these larger scales by combining electric field measurements with an inversion of magnetogram data, for instance, by using the Kamide‐Richmond‐Matsushita (KRM) technique (Kamide et al., 1981). However, both large‐ scale empirical models of ΣP and values calculated through the KRM technique provide unrealistically smoothed values and thus have a limited ability to capture inhomogeneities in ΣP of less than a few hundred kilometers in size. To overcome such limitations, Kosch et al. (1998) related localized ISR conductances to height‐integrated auroral intensities, I, measured by a ground‐based television camera fitted with an interference filter at 557.7 nm. It was proposed that this relationship could allow the conductance to be inferred over the much wider fields of view of any available cameras. The various measurement methods are thus able to examine Pedersen conductances at different scale sizes: ISRs at the 1–10‐km scale and the KRM technique, satellites, and empirical models at scales larger than hundreds of kilometers. The all‐sky imager (ASI) technique pro- posed by Kosch et al. can examine the system at one location at the intermediate scale size of tens to hun- dreds of kilometers, which is valuable in itself, and in addition has the potential to provide such conductance values at multiple locations simultaneously. Although the estimate provided by an ASI may have its limitations, unlike empirical model values, the ASI estimate would not be a time‐averaged value. In addition, unlike satellites, there are always cameras in operation, and cameras are significantly more numerous than the handful of ISRs around the world. With these benefits in mind, it is the purpose of this paper to ask how well Pedersen conductance can be esti- mated from white‐light all‐sky cameras. We derive the relationship between ΣP and I for the white‐light ASIs of the Time History of Events and Macroscale Interactions during Substorms (THEMIS) network. These ASIs form a network over the whole North American continent and so potentially offer the multicamera exploitation proposed by Kosch et al. Due to an ASI cadence of 3 s and near‐zenith spatial resolutions up to 1 km (Mende et al., 2008), the THEMIS network is potentially capable of both capturing some of the smaller‐scale detail in conductance that occurs in dynamic features and also of providing the larger, substorm‐scale context due to the deployment of 26 ASI locations covering 8–12 hr of MLT at auroral lati- tudes.
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